Lecture 5 Flashcards
What is ANOVA and what purpose does it serve?
Analysis of Variance. Allows you to compare ANY number of means.
What rules must be met for ANOVA?
- The samples must all be random or unbiased.
- All samples must be independent of each other.
- Observations within each sample must be independent.
- All of the samples must be drawn from approximately normal populations. If the data in one or more samples are severely non-normal ANOVA cannot be used unless you elect to transform all the data.
- All samples should have approximately equal variances.
What unique circumstance exists for equal variance for ANOVA?
If all sample sizes are exactly the same, tests for equal variance can be ignored.
What is a one way ANOVA?
Looks at group differences based one ONE variable
What is the difference between parametric and nonparametric tests?
Parametric = equal variance assumed Nonparametric = unequal variance
In ANOVA, what does a large F indicate?
Small p value
All F-distributions are skewed ____ and have _____ degrees of freedom
Right, two (one for the numerator and one for the denominator)
How do you calculate df for numerator and denominator in ANOVA?
Numerator df = k - 1 Denominator df = n - k k is the number of groups n is the total number of people in the study
What is the F table
Based on the NDf and DDf, will tell you the critical value needed for significance.
What is a type I error and what is another name for it?
Is it a big deal?
Type I error is considering something different when it is not. aka alpha error
BIG DEAL!
What is a type II error and what is another name for it?
Is it a big deal?
Type II error is considering something not different when it is. aka beta error
Meh.
Type __ errors are considered more deleterious to society and medicine…once you open Pandoras box, its very hard to close (e.g. vaccines cause autism)
Type I errors are considered more deleterious to society and medicine…once you open Pandoras box, its very hard to close (e.g. vaccines cause autism)
What is the most common multiple comparisons test? Is it conservative?
Bonferroni, yes
How do you make a Bonferroni adjustment?
Divide your alpha value by the number of comparisons you wish to make. This is your new p value.
What is the limit of Bonferroni multiple comparisons before it starts to lose power?
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